# Google News Keyword Monitor (`navy_currant/news-radar`) Actor Monitor Google News for any keyword on a schedule. Returns new articles mentioning your term, deduplicated so you only see fresh coverage. Perfect for brand, PR, and competitor monitoring. - **URL**: https://apify.com/navy\_currant/news-radar.md - **Developed by:** [Ishaan](https://apify.com/navy_currant) (community) - **Categories:** Marketing, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Google News Keyword Monitor ๐Ÿ“ฐ **Track any keyword across Google News, automatically.** This actor watches Google News for the terms you care about and returns **new articles** that mention them โ€” deduplicated across runs, so you only ever see fresh coverage, never the same story twice. Set it on a schedule and it becomes a hands-off **news alert feed**: your brand, a competitor, a person, a product, or any topic โ€” delivered to a dataset you can export or pipe into Slack, webhooks, Zapier, and Make. --- ### ๐Ÿ’ก What you can use it for - **Brand & PR monitoring** โ€” catch every news story mentioning your company the moment it publishes. - **Competitor intelligence** โ€” track rivals' launches, funding, and press coverage. - **Reputation management** โ€” get ahead of negative coverage fast. - **Market & topic research** โ€” follow an industry, technology, or trend across thousands of outlets. - **Executive & people tracking** โ€” monitor coverage of a founder, exec, or public figure. ### โœจ Features - ๐Ÿ“ฐ Searches **all of Google News** via its public RSS feed โ€” thousands of sources, always current. - ๐Ÿง  **Deduplicated** โ€” remembers what it has already returned, so scheduled runs surface only new articles. - โฑ๏ธ **Schedule-ready** โ€” run it hourly (or more often) for a continuous news alert stream. - ๐ŸŒ **Language & country** โ€” target any Google News locale (en-US, en-GB, es-ES, โ€ฆ). - ๐Ÿ“ค **Export anywhere** โ€” JSON, CSV, Excel, or push to webhooks / Slack / Zapier / Make. ### ๐Ÿงพ Input | Field | Type | Description | |-------|------|-------------| | `query` | string | The keyword or phrase to watch for. | | `language` | string | Google News language code (e.g. `en-US`). | | `country` | string | Google News country code (e.g. `US`). | | `onlyNewSinceLastRun` | boolean | Suppress articles already returned in earlier runs. | | `maxItems` | integer | Cap on articles per run. | ```json { "query": "your brand name", "language": "en-US", "country": "US", "onlyNewSinceLastRun": true, "maxItems": 50 } ```` ### ๐Ÿ“ฆ Output Each article is one dataset item: `title`, `source`, `url`, `publishedAt`, and `foundAt`. ### โฐ Recommended setup 1. Set `query` to your keyword and turn on `onlyNewSinceLastRun`. 2. Create a **Schedule** (e.g. every hour). 3. Connect an **integration** (Slack, webhook, email, Zapier) to be alerted on new coverage. ### โ“ FAQ **Will I get duplicate articles?** No โ€” with `onlyNewSinceLastRun` on, each run returns only articles it hasn't returned before. **Can I monitor non-US news?** Yes โ€” set `language` and `country` to your locale. **What does it cost?** Pay-per-event: a small charge per run plus per new article returned. *** *Keywords: Google News scraper, news monitoring, brand monitoring, media monitoring, press monitoring, competitor tracking, keyword alerts, news API, PR monitoring, mention tracking.* # Actor input Schema ## `query` (type: `string`): What to watch for in the news (e.g. a brand, company, person, or topic). ## `language` (type: `string`): Google News language code (e.g. en-US, en-GB, es-ES). ## `country` (type: `string`): Google News country code (e.g. US, GB, CA). ## `onlyNewSinceLastRun` (type: `boolean`): Suppress articles already returned in earlier runs, so scheduled runs surface only fresh news. ## `maxItems` (type: `integer`): Safety cap on articles per run. ## Actor input object example ```json { "query": "openai", "language": "en-US", "country": "US", "onlyNewSinceLastRun": true, "maxItems": 50 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "query": "openai" }; // Run the Actor and wait for it to finish const run = await client.actor("navy_currant/news-radar").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "query": "openai" } # Run the Actor and wait for it to finish run = client.actor("navy_currant/news-radar").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "query": "openai" }' | apify call navy_currant/news-radar --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=navy_currant/news-radar", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google News Keyword Monitor", "description": "Monitor Google News for any keyword on a schedule. Returns new articles mentioning your term, deduplicated so you only see fresh coverage. Perfect for brand, PR, and competitor monitoring.", "version": "0.1", "x-build-id": "dgPZV9pZSPmj0b0A2" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/navy_currant~news-radar/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-navy_currant-news-radar", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/navy_currant~news-radar/runs": { "post": { "operationId": "runs-sync-navy_currant-news-radar", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/navy_currant~news-radar/run-sync": { "post": { "operationId": "run-sync-navy_currant-news-radar", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "query" ], "properties": { "query": { "title": "Keyword / phrase", "type": "string", "description": "What to watch for in the news (e.g. a brand, company, person, or topic)." }, "language": { "title": "Language", "type": "string", "description": "Google News language code (e.g. en-US, en-GB, es-ES).", "default": "en-US" }, "country": { "title": "Country", "type": "string", "description": "Google News country code (e.g. US, GB, CA).", "default": "US" }, "onlyNewSinceLastRun": { "title": "Only new since last run", "type": "boolean", "description": "Suppress articles already returned in earlier runs, so scheduled runs surface only fresh news.", "default": true }, "maxItems": { "title": "Max items per run", "maximum": 100, "type": "integer", "description": "Safety cap on articles per run.", "default": 50 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```